In this paper, we consider a radio resource management (RRM) problem in the dynamic wireless networks, comprising multiple communication links that share the same spectrum resource. To achieve high network throughput while ensuring fairness across all links, we formulate a resilient power optimization problem with per-user minimum-rate constraints. We obtain the corresponding Lagrangian dual problem and parameterize all variables with neural networks, which can be trained in an unsupervised manner due to the provably acceptable duality gap. We develop a meta-learning approach with graph neural networks (GNNs) as parameterization that exhibits fast adaptation and scalability to varying network configurations. We formulate the objective of meta-learning by amalgamating the Lagrangian functions of different network configurations and utilize a first-order meta-learning algorithm, called Reptile, to obtain the meta-parameters. Numerical results verify that our method can efficiently improve the overall throughput and ensure the minimum rate performance. We further demonstrate that using the meta-parameters as initialization, our method can achieve fast adaptation to new wireless network configurations and reduce the number of required training data samples.
xApp Empowered Resource Management for Non-Terrestrial Users in 5G O-RAN Networks
School of Electronic and Electrical Engineering, University of Leeds（利兹大学电子与电气工程学院）；College of Electronics Engineering, Ninevah University（尼尼微大学电子工程学院）
Artificial Intelligence Empowered Multiple Access for Ultra Reliable and Low Latency THz Wireless Networks
University of Piraeus（比雷埃夫斯大学）；RapidMiner GmbH（RapidMiner有限公司）；Nokia Standardization Department（诺基亚标准化部）；Université Paris-Saclay（巴黎萨克雷大学）；CNRS（法国国家科学研究中心）；CentraleSupélec（巴黎中央理工-高等电力学院）
Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks
The Institute for Artificial Intelligence Research and Development of Serbia（塞尔维亚人工智能研发研究所）；University of East Sarajevo（东萨拉热窝大学）；University of Sarajevo（萨拉热窝大学）；Trinity College Dublin（都柏林圣三一学院）；University of Novi Sad（诺维萨德大学）
